2026 Intern Research Scientist – AI-powered Aut...
@ IBM

San Jose, CA
$50,000
On Site
Intern
Posted 11 hours ago

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Introduction

IBM Research takes responsibility for technology and its role in society. Joining IBM Research means working on urgent, mind-bending tech that shapes generations. You will be part of a team that invents what's next in computing, driving discovery and real-world impact.

Your Role And Responsibilities

The 2026 Intern Research Scientist – AI-powered Automation will help advance IBM's research and development agenda in artificial intelligence and foundation models. Areas of focus include Natural Language Processing, Distributed (Edge) AI, Trusted AI, Scalable Data Engineering, AI for Business and IT Automation, AI Applications, AI Security, AI Hardware, Automated AI, Conversational AI, and API Composition and Orchestration.

You will collaborate closely with other researchers and engineers to conduct world-class research and software development with the goal of publishing results at top academic venues.

Preferred Education & Experience

Candidates should have a Master’s Degree and demonstrated interest in research and publication. Experience in AI, programming, cloud-native development, and machine learning engineering is essential.

Technical Expertise

  • Proficient in coding languages: Python, Java, C/C++, JavaScript, R.
  • Experienced with agile practices, Docker, Kubernetes, and OpenShift.
  • Skilled in machine learning toolkits such as PyTorch, TensorFlow, and scikit-learn.
  • Knowledgeable in backend storage and NoSQL databases.

Key Skills/Competency

  • AI Research
  • Machine Learning
  • Natural Language Processing
  • Cloud-native Development
  • Software Engineering
  • Data Engineering
  • Algorithm Design
  • Research Publication
  • Collaborative Work
  • Technical Communication
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How to Get Hired at IBM

🎯 Tips for Getting Hired

  • Customize your resume: Highlight AI research and programming projects.
  • Showcase publications: Emphasize published work in top venues.
  • Demonstrate expertise: Mention experience with cloud-native tools.
  • Prepare for interviews: Review AI and ML technical questions.

📝 Interview Preparation Advice

Technical Preparation

Review Python and Java fundamentals.
Practice using ML toolkits like TensorFlow.
Study algorithm design and system validation.
Familiarize with cloud-native container tools.

Behavioral Questions

Describe team collaboration experiences.
Explain your problem-solving approach.
Detail a challenging research project.
Discuss handling constructive feedback.

Frequently Asked Questions